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Autoimmune hepatitis risk prediction model and construction method thereof

An autoimmunity and risk prediction technology, applied in the field of autoimmune hepatitis risk prediction model and its construction, can solve the problems that AIH patients cannot receive early diagnosis and timely treatment, and achieve the effect of high resolution

Pending Publication Date: 2020-10-13
SHANGHAI SIXTH PEOPLES HOSPITAL
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, many AIH patients cannot receive early diagnosis and timely treatment
At present, there is no recognized effective method that can improve the compliance of liver biopsy in patients with unexplained liver damage.

Method used

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  • Autoimmune hepatitis risk prediction model and construction method thereof
  • Autoimmune hepatitis risk prediction model and construction method thereof
  • Autoimmune hepatitis risk prediction model and construction method thereof

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0066] This embodiment provides a method for constructing an autoimmune hepatitis risk prediction model, and the specific steps are as follows:

[0067] Step 1, through the selection and classification of cases of unexplained liver damage, non-invasive clinical data were collected:

[0068] 1. Case selection and classification

[0069] The case inclusion criteria were: all patients were diagnosed with unexplained liver damage, and all patients had undergone liver biopsy pathological examination; the exclusion criteria were: younger than 18 years old; positive markers of hepatitis virus and in line with the diagnosis of viral hepatitis; in line with alcoholic liver disease or Diagnosis of drug-induced liver injury; immunomodulatory drugs (such as hormones, azathioprine, etc.) were used for diagnosis and treatment before biopsy.

[0070] Noninvasive clinical data and liver biopsy data were collected from 2005 to 2019. Among them, 111 cases were in the Sixth People's Hospital A...

Embodiment 2

[0094] This embodiment uses the Youden index (sensitivity+specificity-1) to determine the cut-off value of the training cohort, the calculated cut-off value is 0.44, and adopts real cases to measure the accuracy of nomogram by sensitivity and specificity, and then evaluates the nomogram Authenticity, thus verifying that the nomogram model can be used clinically.

[0095] According to the cut-off value, this example successfully predicted 16 out of 20 true AIH patients and 55 out of 72 true NAIH people. According to the prediction results, the sensitivity was 80%, the specificity was 76.39%, the positive predictive value was 48.48%, the negative predictive value was 93.22%, and the accuracy was 77.17%. The results are good and can be used clinically.

[0096] In summary, the present invention provides a risk prediction model of autoimmune hepatitis and its construction method. Through the selection and classification of cases of liver damage of unknown cause, non-invasive clin...

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Abstract

The invention provides an autoimmune hepatitis risk prediction model and a construction method thereof. According to the construction method, noninvasive clinical data are collected and multi-factor logistic regression analysis is performed by selecting and classifying unknown-cause liver damage cases to obtain risk factors and decision coefficients of AIH, and a logistic regression model for predicting the autoimmune hepatitis risk is obtained, or an autoimmune hepatitis risk prediction nomogram model is established by the logistic regression. The autoimmune hepatitis risk prediction model provided by the invention can be used for early risk prediction of AIH of a patient with unknown-cause liver damage, has higher resolution, accuracy and clinical application value, is helpful for doctors to effectively persuade the patient with unknown-cause liver damage to receive the suggestion of liver biopsy as soon as possible, and enables the real patient with autoimmune hepatitis to be diagnosed and treated properly.

Description

technical field [0001] The invention relates to the field of biotechnology, in particular to an autoimmune hepatitis risk prediction model and a construction method thereof. Background technique [0002] The annual incidence and prevalence of autoimmune hepatitis (AIH) are low. The Asia-Pacific region is 0.67-2.0 / 100000 and 3-24.5 / 100000 respectively. The occurrence of AIH may be related to multiple genes, age, gender and other factors, but it is still difficult to accurately quantify its risk factors [1-3] . In the early stages of AIH, the symptoms of the disease are usually mild—fatigue, loss of appetite, jaundice, nausea, itchy skin, joint pain—and sometimes go away on their own and then recur [4-6] . This condition may go on for years without the patient noticing. Therefore, some AIH patients manifest the so-called "unexplained liver damage" in the early stage, and may not be able to receive timely and accurate diagnosis and treatment. And when the patient sees the...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/30
CPCG16H50/30
Inventor 胡建军
Owner SHANGHAI SIXTH PEOPLES HOSPITAL
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